Skill and heuristics are alternative sources of intuitive judgments and choices.
This is the essence of intuitive heuristics: when faced with a difficult question, we often answer an easier one instead, usually without noticing the substitution.
System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental activities that demand it, including complex computations. The operations of System 2 are often associated with the subjective experience of agency, choice, and concentration. Most of what you (your System 2) think and do originates in your System 1, but System 2 takes over when things get difficult, and it normally has the last word.
A crucial capability of System 2 is the adoption of "task sets": it can program memory to obey an instruction that overrides habitual responses.
Self-control and deliberate thought apparently draw on the same limited budget of effort.
Cognitive load is not the only cause of weakened self-control. A few drinks have the same effect, as does a sleepless night. The self-control of morning people is impaired at night; the reverse is true of night people. Too much concern about how well one is doing in a task sometimes disrupts performance by loading short-term memory with pointless anxious thoughts. The conclusion is straightforward: self-control requires attention and effort. Another way of saying this is that controlling thoughts and behaviors is one of the tasks that System 2 performs.
The idea of money primes individualism: a reluctance to be involved with others, to depend on others, or to accept demands from others.
Predictable illusions inevitably occur if a judgment is based on an impression of cognitive ease or strain. Anything that makes it easier for the associative machine to run smoothly will also bias beliefs.
If you care about being thought credible and intelligent, do not use complex language where simpler language will do.
How do you know that a statement is true? If it is strongly linked by logic or association to other beliefs or preferences you hold, or comes from a source you trust and like, you will feel a sense of cognitive ease. The trouble is that there may be other causes for your feeling of ease--including the quality of the font and the appealing rhythm of the prose--and you have no simple way of tracing your feelings to their source. The sense of ease or strain has multiple causes, and it is difficult to tease them apart.
Good mood, intuition, creativity, gullibility, and increased reliance on System 1 form a cluster. At the other pole, sadness, vigilance, suspicion, an analytic approach, and increased effort also go together. A happy mood loosens the control of System 2 over performance: when in a good mood, people become more intuitive and more creative but also less vigilant and more prone to logical errors.
Speaking of Cognitive Ease
"We must be inclined to believe it because it has been repeated so often, but let's think it through again."
"I'm in a very good mood today, and my System 2 is weaker than usual. I should be extra careful."
To derive the most useful information from multiple sources of evidence, you should always try to make these sources independent of each other. This rule is part of good police procedure.
Jumping to conclusions on the basis of limited evidence is so important to an understanding of intuitive thinking, and comes up so often in this book, that I will use a cumbersome abbreviation for it: WYSIATI, which stands for what you see is all there is. System 1 is radically insensitive to both the quality and the quantity of the information that gives rise to impressions and intuitions.
It is the consistency of the information that matters for a good story, not its completeness. Indeed, you will often find that knowing little makes it easier to fit everything you know into a coherent pattern.
Good mood and cognitive ease are the human equivalents of assessments of safety and familiarity.
I propose a simple account of how we generate intuitive opinions on complex matters. If a satisfactory answer to a hard question is not found quickly, System 1 will find a related question that is easier and will answer it. I call the operation of answering one question in place of another substitution. I also adopt the following terms: The target question is the assessment you intend to produce. The heuristic question is the simpler question that you answer instead. The technical definition of heuristic is a simple procedure that helps find adequate, though often imperfect, answers to difficult questions. The word comes from the same root as eureka.
Characteristics of System 1
Even now, you must exert some mental effort to see that the following two statements mean exactly the same thing: Large samples are more precise than small samples. Small samples yield extreme results more often than large samples do. The first statement has a clear ring of truth, but until the second version makes intuitive sense, you have not truly understood the first.
People are not adequately sensitive to sample size. The strong bias toward believing that small samples closely resemble the population from which they are drawn is also part of a larger story: we are prone to exaggerate the consistency and coherence of what we see. The exaggerated faith of researchers in what can be learned from a few observations is closely related to the halo effect, the sense we often get that we know and understand a person about whom we actually know very little. System 1 runs ahead of the facts in constructing a rich image on the basis of scraps of evidence. A machine for jumping to conclusions will act as if it believed in the law of small numbers. More generally, it will produce a representation of reality that makes too much sense. The associative machinery seeks causes. The difficulty we have with statistical regularities is that they call for a different approach. Instead of focusing on how the event at hand came to be, the statistical view relates it to what could have happened instead. Nothing in particular caused it to be what it is--chance selected it from among its alternatives.
We are far too willing to reject the belief that much of what we see in life is random.
The exaggerated faith in small samples is only one example of a more general illusion--we pay more attention to the content of messages than to information about their reliability, and as a result end up with a view of the world around us that is simpler and more coherent than the data justify. Jumping to conclusions is a safer sport in the world of our imagination than it is in reality. Statistics produce many observations that appear to beg for causal explanations but do not lend themselves to such explanations. Many facts of the world are due to chance, including accidents of sampling. Causal explanations of chance events are inevitably wrong.
A message, unless it is immediately rejected as a lie, will have the same effect on the associative system regardless of its reliability. The gist of the message is the story, which is based on whatever information is available, even if the quantity of the information is slight and its quality is poor: WYSIATI.
You should assume that any number that is on the table has had an anchoring effect on you, and if the stakes are high you should mobilize yourself (your System 2) to combat the effect.
Speaking of Anchors
"Plans are best-case scenarios. Let's avoid anchoring on plans when we forecast actual outcomes. Thinking about ways the plan could go wrong is one way to do it."
We define the availability heuristic as the process of judging frequency by "the ease with which instances come to mind." The availability heuristic, like other heuristics of judgment, substitutes one question for another: you wish to estimate the size of a category or the frequency of an event, but you report an impression of the ease with which instances come to mind. Substitution of questions inevitably produces systematic errors.
You must make the effort to reconsider your impressions and intuitions by asking such questions as, "Is our belief that theft by teenagers is a major problem due to a few recent instances in our neighborhood?" or "Could it be that I feel no need to get a flu shot because none of my acquaintances got the flu last year?" Maintaining one's vigilance against biases is a chore--but the chance to avoid a costly mistake is sometimes worth the effort.
The world in our heads is not a precise replica of reality; our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed. The affect heuristic is an instance of substitution, in which the answer to an easy question (How do I feel about it?) serves as an answer to a much harder question (What do I think about it?).
A basic limitation in the ability of our mind to deal with small risks: we either ignore them altogether or give them far too much weight--nothing in between.
The essential keys to disciplined Bayesian reasoning can be simply summarized: Anchor your judgment of the probability of an outcome on a plausible base rate. Question the diagnosticity of your evidence.
People who are taught surprising statistical facts about human behavior may be impressed to the point of telling their friends about what they have heard, but this does not mean that their understanding of the world has really changed. The test of learning psychology is whether your understanding of situations you encounter has changed, not whether you have learned a new fact. There is a deep gap between our thinking about statistics and our thinking about individual cases.
A significant fact of the human condition: the feedback to which life exposes us is perverse. Because we tend to be nice to other people when they please us and nasty when they do not, we are statistically punished for being nice and rewarded for being nasty.
Whenever the correlation between two scores is imperfect, there will be regression to the mean.
Intuitive predictions need to be corrected because they are not regressive and therefore are biased. Suppose that I predict for each golfer in a tournament that his score on day 2 will be the same as his score on day 1. This prediction does not allow for regression to the mean: the golfers who fared well on day 1 will on average do less well on day 2, and those who did poorly will mostly improve. When they are eventually compared to actual outcomes, nonregressive predictions will be found to be biased. They are on average overly optimistic for those who did best on the first day and overly pessimistic for those who had a bad start. The predictions are as extreme as the evidence.
The biases we find in predictions that are expressed on a scale, such as GPA or the revenue of a firm, are similar to the biases observed in judging the probabilities of outcomes. The corrective procedures are also similar: Both contain a baseline prediction, which you would make if you knew nothing about the case at hand. In the categorical case, it was the base rate. In the numerical case, it is the average outcome in the relevant category. Both contain an intuitive prediction, which expresses the number that comes to your mind, whether it is a probability or a GPA. In both cases, you aim for a prediction that is intermediate between the baseline and your intuitive response. In the default case of no useful evidence, you stay with the baseline. At the other extreme, you also stay with your initial predictiononsр. This will happen, of course, only if you remain completely confident in your initial prediction after a critical review of the evidence that supports it. In most cases you will find some reason to doubt that the correlation between your intuitive judgment and the truth is perfect, and you will end up somewhere between the two poles. This procedure is an approximation of the likely results of an appropriate statistical analysis. If successful, it will move you toward unbiased predictions, reasonable assessments of probability, and moderate predictions of numerical outcomes. The two procedures are intended to address the same bias: intuitive predictions tend to be overconfident and overly extreme.
We will not learn to understand regression from experience. Even when a regression is identified, as we saw in the story of the flight instructors, it will be given a causal interpretation that is almost always wrong.
Narrative fallacies arise inevitably from our continuous attempt to make sense of the world. The explanatory stories that people find compelling are simple; are concrete rather than abstract; assign a larger role to talent, stupidity, and intentions than to luck; and focus on a few striking events that happened rather than on the countless events that failed to happen. Any recent salient event is a candidate to become the kernel of a causal narrative.
The ultimate test of an explanation is whether it would have made the event predictable in advance.
You cannot help dealing with the limited information you have as if it were all there is to know. You build the best possible story from the information available to you, and if it is a good story, you believe it. Paradoxically, it is easier to construct a coherent story when you know little, when there are fewer pieces to fit into the puzzle. Our comforting conviction that the world makes sense rests on a secure foundation: our almost unlimited ability to ignore our ignorance.
Your inability to reconstruct past beliefs will inevitably cause you to underestimate the extent to which you were surprised by past events (hindsight bias).
Hindsight bias has pernicious effects on the evaluations of decision makers. It leads observers to assess the quality of a decision not by whether the process was sound but by whether its outcome was good or bad.
Subjective confidence in a judgment is not a reasoned evaluation of the probability that this judgment is correct. Confidence is a feeling, which reflects the coherence of the information and the cognitive ease of processing it. It is wise to take admissions of uncertainty seriously, but declarations of high confidence mainly tell you that an individual has constructed a coherent story in his mind, not necessarily that the story is true.
The diagnostic for the existence of any skill is the consistency of individual differences in achievement.
The illusion that we understand the past fosters overconfidence in our ability to predict the future.
Hedgehogs "know one big thing" and have a theory about the world; they account for particular events within a coherent framework, bristle with impatience toward those who don't see things their way, and are confident in their forecasts. They are also especially reluctant to admit error. For hedgehogs, a failed prediction is almost always "off only on timing" or "very nearly right." They are opinionated and clear, which is exactly what television producers love to see on programs. Two hedgehogs on different sides of an issue, each attacking the idiotic ideas of the adversary, make for a good show. Foxes, by contrast, are complex thinkers. They don't believe that one big thing drives the march of history (for example, they are unlikely to accept the view that Ronald Reagan single-handedly ended the cold war by standing tall against the Soviet Union). Instead the foxes recognize that reality emerges from the interactions of many different agents and forces, including blind luck, often producing large and unpredictable outcomes.
The confidence that people have in their intuitions is not a reliable guide to their validity. In other words, do not trust anyone--including yourself--to tell you how much you should trust their judgment.
If subjective confidence is not to be trusted, how can we evaluate the probable validity of an intuitive judgment? When do judgments reflect true expertise? When do they display an illusion of validity? The answer comes from the two basic conditions for acquiring a skill: an environment that is sufficiently regular to be predictable and opportunity to learn these regularities through prolonged practice When both these conditions are satisfied, intuitions are likely to be skilled. Chess is an extreme example of a regular environment, but bridge and poker also provide robust statistical regularities that can support skill. In contrast, stock pickers and political scientists who make long-term forecasts operate in a zero-validity environment. Their failures reflect the basic unpredictability of the events that they try to forecast.
Whether professionals have a chance to develop intuitive expertise depends essentially on the quality and speed of feedback, as well as on sufficient opportunity to practice.
Two profoundly different approaches to forecasting: the inside view and the outside view.
This is a common pattern: people who have information about an individual case rarely feel the need to know the statistics of the class to which the case belongs.
When forecasting the outcomes of risky projects, executives too easily fall victim to the planning fallacy. In its grip, they make decisions based on delusional optimism rather than on a rational weighting of gains, losses, and probabilities. They overestimate benefits and underestimate costs. They spin scenarios of success while overlooking the potential for mistakes and miscalculations.
Overconfidence is another manifestation of WYSIATI: when we estimate a quantity, we rely on information that comes to mind and construct a coherent story in which the estimate makes sense. Allowing for the information that does not come to mind--perhaps because one never knew it--is impossible.
An unbiased appreciation of uncertainty is a cornerstone of rationality--but it is not what people and organizations want. Extreme uncertainty is paralyzing under dangerous circumstances, and the admission that one is merely guessing is especially unacceptable when the stakes are high. Acting on pretended knowledge is often the preferred solution.
Theory-induced blindness: once you have accepted a theory and used it as a tool in your thinking, it is extraordinarily difficult to notice its flaws. If you come upon an observation that does not seem to fit the model, you assume that there must be a perfectly good explanation that you are somehow missing. You give the theory the benefit of the doubt, trusting the community of experts who have accepted it.
You know you have made a theoretical advance when you can no longer reconstruct why you failed for so long to see the obvious.
The probability of a rare event is most likely to be overestimated when the alternative is not fully specified.
A rich and vivid representation of the outcome, whether or not it is emotional, reduces the role of probability in the evaluation of an uncertain prospect. This hypothesis suggests a prediction, in which I have reasonably high confidence: adding irrelevant but vivid details to a monetary outcome also disrupts calculation.
The asymmetry in the risk of regret favors conventional and risk-averse choices.
You can take precautions that will inoculate you against regret. Perhaps the most useful is to be explicit about the anticipation of regret. If you can remember when things go badly that you considered the possibility of regret carefully before deciding, you are likely to experience less of it. You should also know that regret and hindsight bias will come together, so anything you can do to preclude hindsight is likely to be helpful. My personal hindsight-avoiding policy is to be either very thorough or completely casual when making a decision with long-term consequences. Hindsight is worse when you think a little, just enough to tell yourself later, "I almost made a better choice."
A bad outcome is much more acceptable if it is framed as the cost of a lottery ticket that did not win than if it is simply described as losing a gamble. We should not be surprised: losses evokes stronger negative feelings than costs. Choices are not reality-bound because System 1 is not reality-bound.
Decision makers tend to prefer the sure thing over the gamble (they are risk averse) when the outcomes are good. They tend to reject the sure thing and accept the gamble (they are risk seeking) when both outcomes are negative.
Any aspect of life to which attention is directed will loom large in a global evaluation. This is the essence of the focusing illusion, which can be described in a single sentence: Nothing in life is as important as you think it is when you are thinking about it.
It is logical to describe the life of the experiencing self as a series of moments, each with a value. The value of an episode--I have called it a hedonimeter total--is simply the sum of the values of its moments. But this is not how the mind represents episodes. The remembering self, as I have described it, also tells stories and makes choices, and neither the stories nor the choices properly represent time. In storytelling mode, an episode is represented by a few critical moments, especially the beginning, the peak, and the end. Duration is neglected.
The acquisition of skills requires a regular environment, an adequate opportunity to practice, and rapid and unequivocal feedback about the correctness of thoughts and actions. When these conditions are fulfilled, skill eventually develops, and the intuitive judgments and choices that quickly come to mind will mostly be accurate. All this is the work of System 1, which means it occurs automatically and fast. A marker of skilled performance is the ability to deal with vast amounts of information swiftly and efficiently.
The way to block errors that originate in System 1 is simple in principle: recognize the signs that you are in a cognitive minefield, slow down, and ask for reinforcement from System 2. Unfortunately, this sensible procedure is least likely to be applied when it is needed most. The voice of reason may be much fainter than the loud and clear voice of an erroneous intuition, and questioning your intuitions is unpleasant when you face the stress of a big decision. More doubt is the last thing you want when you are in trouble. The upshot is that it is much easier to identify a minefield when you observe others wandering into it than when you are about to do so. Observers are less cognitively busy and more open to information than actors. That was my reason for writing a book that is oriented to critics and gossipers rather than to decision makers.
Whatever else it produces, an organization is a factory that manufactures judgments and decisions. Every factory must have ways to ensure the quality of its products in the initial design, in fabrication, and in final inspections. The corresponding stages in the production of decisions are the framing of the problem that is to be solved, the collection of relevant information leading to a decision, and reflection and review. An organization that seeks to improve its decision product should routinely look for efficiency improvements at each of these stages. The operative concept is routine. Constant quality control is an alternative to the wholesale reviews of processes that organizations commonly undertake in the wake of disasters. There is much to be done to improve decision making.
There is a direct link from more precise gossip at the watercooler to better decisions. Decision makers are sometimes better able to imagine the voices of present gossipers and future critics than to hear the hesitant voice of their own doubts. They will make better choices when they trust their critics to be sophisticated and fair, and when they expect their decision to be judged by how it was made, not only by how it turned out.